ArticleJournal of nuclear medicine : official publication, Society of Nuclear Medicine2022
Evaluation of Data-Driven Rigid Motion Correction in Clinical Brain PET Imaging.
Article in Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 28 citations in OpenAlex.
- Attenuation Pre-Correction in Iterative PET Image Reconstruction: What is the Statistical Cost?IEEE transactions on radiation and plasma medical sciences · 2026Article
- Time-resolved PET imaging using a joint dynamic reconstruction and motion estimation framework (DREME-PET).Medical physics · 2026Article
- Technical Optimization Strategies for Amyloid PET Under Challenging Acquisition Conditions: A Comprehensive Narrative Review.Diagnostics (Basel, Switzerland) · 2026Review
- Quantitative evaluation of radiotherapy accuracy in head and neck cancer: correcting cbct image distortions for improved tumour targeting and dose assessment.Physical and engineering sciences in medicine · 2026Article
- Correcting fast irregular motion in PET: maximum-likelihood motion and activity (MLMA) reconstruction.EJNMMI physics · 2026Article
- The impact of data driven motion correction for clinical brain PET/MRI radiotracers.EJNMMI physics · 2026Article
- Enhancing the Diagnostic Accuracy of Amyloid PET: The Impact of MR-Guided PET Reconstruction.IEEE transactions on radiation and plasma medical sciences · 2026Article
- PET Head Motion Estimation Using Supervised Deep Learning With Attention.IEEE transactions on medical imaging · 2026Article
- Eagle eyes on the human brain and beyond: PET at ultra-high spatial resolution.European journal of nuclear medicine and molecular imaging · 2026Article
- Quantitative validation of data-driven motion correction for brain PET using phantom with motion generator system.EJNMMI physics · 2025Article
- Motion study on upright patient positioning in walk-through PET: evaluation in a clinical setting.EJNMMI physics · 2025Article
- A Novel Method in PET Image Reconstruction Using MRI Anatomical Priors.IEEE transactions on radiation and plasma medical sciences · 2025Article
- Validation of a data-driven motion-compensated PET brain image reconstruction algorithm in clinical patients using four radiotracers.EJNMMI physics · 2025Article
- Future prospects for image-derived input function in molecular imaging quantification with the 7 T MR-BrainPET insert.Frontiers in neuroscience · 2025Article
- Impact of upgrading from a 25-cm to a 30-cm z-axis field of view digital PET/CT in a pediatric hospital.Pediatric radiology · 2024Article
- Improving diagnostic precision in amyloid brain PET imaging through data-driven motion correction.EJNMMI physics · 2024Article
- Motion-correction strategies for enhancing whole-body PET imaging.Frontiers in nuclear medicine · 2024Article
- Article
- Markerless head motion tracking and event-by-event correction in brain PET.Physics in medicine and biology · 2023Article
- Impact of motion correction on [Physics in medicine and biology · 2023Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Head motion during brain PET imaging can significantly degrade the quality of the reconstructed image, leading to reduced diagnostic value and inaccurate quantitation. A fully data-driven motion correction approach was recently demonstrated to produce highly accurate motion estimates (<1 mm) with high temporal resolution (≥1 Hz), which can then be used for a motion-corrected reconstruction. This can be applied retrospectively with no impact on the clinical image acquisition protocol. We present a reader-based evaluation and an atlas-based quantitative analysis of this motion correction approach within a clinical cohort.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.